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Activity Number: 344
Type: Topic Contributed
Date/Time: Tuesday, August 11, 2015 : 10:30 AM to 12:20 PM
Sponsor: Korean International Statistical Society
Abstract #316923 View Presentation
Title: Zero-Inflated Quantile Regression with Its Application in NOMAS
Author(s): Ying Wei* and Ken Cheung
Companies: Columbia University and Columbia University
Keywords: quantile regression ; prediction ; zero-inflated data
Abstract:

The Northern Manhattan Study (NOMAS) is a population-based study designed to evaluate the impact of medical, socio-economic, and other risk factors on the incidence of vascular disease in a multi-ethnic, stroke-free cohort, consisting of 3,298 participants recruited between 1993 and 2001. In NOMAS, building a reliable prediction model for plaque burden will lead to improved prediction of stroke outcome in distant future. Carotid plaque measurements for total plaque area and density were available via high-resolution B-mode ultrasounds in NOMAS. These plaque phenotypes (area and density) take on non-negative values, with a point mass at 0 for subjects who did not have a plaque. In this application, we propose quantile regression model for zero-inflated, non-negative data. The quantile regression provides a natural modeling framework for non-normal data, and offers a semi-parametric approach that allows for robust prediction.


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